The Prediction Model of Cotton Yarn Quality Based on Artificial Recurrent Neural Network

Abstract

It is key index of cotton yarn quality such as cotton yarn strength and so on. It can well control cotton yarn quality by predicting yarn strength and so on. Generally, it is normal used to predict yarn strength such as Multiple Linear Regression (MLR), Support Vector Regression (SVR) and shallow Artificial Neural Network (ANN). Because the processing of cotton yarn production has time sequence, the paper proposes a new deep neural network, it is artificial Recurrent Neural Network (RNN). It used 1800 sets of data to train RNN, SVR and ANN. It tested RNN, MLR, SVR and ANN with 200 sets of data. Experimental results show that the Recurrent Neural Network (RNN) is the best accuracy among these four algorithms.